Data Scientist, Alexa, Alexa Health

Key Skills

Java Programming, Design, Python Programming, Apache, Database, SQL, AWS, Apache Hadoop, Data science techniques, MATLAB Programming, Natural Language Processing (NLP), NoSQL, R Programming, Algorithms, SPARK Programming, SAS, RNNs, Large scale data processing, ETL frameworks, Common data structures

Job Description

Do you want to drive innovation in the healthcare space and make a positive difference in people's lives? Are you passionate about creating innovative solutions to make Alexa a trusted health assistant for millions of customers? Are you excited about utilizing statistical analysis, machine learning, data mining, and leverage tons of Amazon data to learn and help millions of people? If so, you have found the right match! Alexa Health & Wellness team is looking for a Data Scientist II (DS) to innovate across broad machine learning areas from new language models (for improved natural language understanding accuracy in complex environments) to personalized recommendation services based on real time data.

An ideal candidate will be an expert in the areas of machine learning and statistics who will have expertise in applying theoretical models in an applied environment. The candidate will be expected to work on numerous aspects of Machine Learning such as feature engineering, predictive modeling, scalable inference methods, and deep learning.

Key job responsibilities

• Work on complex Science problems and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to design and implement software solutions for science problems
• Design, implement, test, deploy, and maintain FSTs and innovative data and machine learning solutions
• Research and develop models and tools to support strategic and tactical decision-making
• Collaborate with data and software engineers to implement the design of data architecture and to automate and scale statistical analyses
• Ability to convey mathematical results to non-science stakeholders and strength in clarifying and formalizing complex problems
• Superior verbal and written communication and presentation skills and ability to convey rigorous mathematical concepts and considerations to non-experts
• A day in the life
• You will be working with the product manager to gather requirements, collect data from various resources and define functional requirements for the proposed features.
• You will develop FSTs and statistical models and release them to the production environment.
• Continue monitoring the performance of the model and improve it over time.

About the team

Alexa is Amazon’s cloud-based voice service available on more than 100 million devices. Alexa holds the promise to enable novel applications across versatile domains. We are building a new team (Alexa Health & Wellness) to develop innovative solutions to make Alexa a trusted health assistant for millions of customers. We build data solutions that leverage voice and AI to help millions of people live longer and healthier lives. In the last year, we launched features focused on medication management, mental health, and COVID19. We have an exciting roadmap and we are just getting started!

BASIC QUALIFICATIONS

Bachelor's Degree

• 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
• 2 years working as a Data Scientist
• 1+ years of experience working in data science, statistical learning, deep learning, natural language understanding, or related disciplines.

PREFERRED QUALIFICATIONS

• Experience working with modern tools for big data storage and analysis (e.g., AWS, Apache Spark, Hadoop, NoSQL)
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
• Understanding of Computer Science fundamentals of data structures, object-oriented design, algorithm design, and complexity analysis.
• Hands on experience in building deep learning and natural language models, especially RNNs (LSTM, BiLSTM, etc.)
• Experience in ETL and databases in a business environment with large-scale, complex datasets
• Experience with defining research and development practices in an applied environment